Non-cooperative demodulation is a technique to demodulate communication signals without hand shaking between the transmitter and the receiver. This technique has been widely used in both military and commercial communications, battlefield surveillance, hostile signal detection, and signal monitoring. In non-cooperative communications, the receiver has no knowledge, or only has limited knowledge of the transmitting signal, for example the signal monitoring devices may not know the format of the signal being monitored in tactical or hostile environment involving military or law enforcement operations. Non-cooperative demodulation will be used in non-cooperative communication.
Automatic modulation classification is a key component in non-cooperative demodulation for recognizing the modulation scheme of a transmitted signal without prior knowledge of the signal ground truth and cueing the software-defined radio to choose the proper built-in demodulator. Although significant research has been conducted on automatic modulation classification methods during the last two decades, this research has been limited to single receiver situations where the classification performance and recognition of a successful rate have largely depended on channel quality and the receiver signal strength. These conditions do not ordinarily apply to non-cooperative communications because in a non-cooperative communication environment, particularly in military applications, the received signal at the single sensor is usually very weak so that the single sensor modulation classification of an unknown weak signal is usually difficult and unreliable.
Further, prior art automatic modulation classification devices and methods do not adequately account for multiple receiver situations such as sensor networks, whose uses have become more and more popular. Due to the dramatic and widespread use of sensor networks, single sensor monitoring is now considered to be inadequate.
Thus, there has been a long-felt need for better signal monitoring techniques that lead to more effective modulation classification of weak signals without suffering from the limitations, shortcomings and difficulties of single receiver configurations such as receiving weak signals and classifying the unknown weak signal.
The general principles of SDRs and modulation classifications or schemes are presented in the following publications which are incorporated herein in their entirety: Y. Huang and A. Polydoros, Likelihood methods for MPSK modulation classification. IEEE Trans. Commun., vol. 43, 1493-1504; J. Sills, Maximum-likelihood modulation classification for PSK/QAM. Proc. MILCOM'99, 1999, 57-61; K. Umebayshi et al., “Blind estimation of the modulation scheme adapted to noise power based on a concept of software define radio,” in Proc. in European Wireless 2002(EW2002), pp.829-834 (2002-02); O. Menguc and F. Jondral, “Air interface recognition for a software radio system exploiting cyclostationarity,” in Proc. of the 15th IEEE Personal, Indoor and Mobile Radio Communications, Vol. 3, September 2004, pp.1947-1951.
Automatic modulation classification methods are also discussed in “Real-time Modulation Classification Based on Maximum Likelihood,” by Wei Su, Jefferson L. Xu and Mengchu Zhou. This publication was presented to the IEEE in about November 2008 and is incorporated herein in its entirety. Further discussion of software-defined radio and modulation recognition is presented in “Software Defined Radio Equipped with Rapid Modulation Recognition” by Wei Su, Senior Member, IEEE, Jefferson L. Xu and Mengchu Zhou, Fellow, IEEE, which is also incorporated herein in its entirety. The latter publication was also presented to the IEEE in about October 2009.